# Jason Brenier, Ph.D. > Chief AI Officer, Product Leader & Linguist | Enterprise AI Platforms, NLP & Agentic Systems, Portfolio Value Creation Location: San Francisco, California, United States Profile: https://flows.cv/jasonbrenierphd As an innovative tech investor, AI leader, and operator, I develop investment theses for emerging technologies, setting the strategic vision to bridge AI capabilities, ethics, and organizational goals. Leading interdisciplinary technology teams across VC, finance and legal, I inspire cross-functional innovation and product development initiatives that drive impact within businesses. From spearheading VC initiatives and creating global enterprise AI software to developing deal origination and sales products, my strategies enhance deal flow and accelerate startup growth. As a transformational leader, I foster an innovative culture and support startups and portfolio companies through venture creation and growth lifecycles. ## Work Experience ### Co-founder, Chief AI Officer @ Ground Truth Systems Jan 2025 – Present | San Francisco, CA Drive product and ML roadmap for agentic SaaS platform orchestrating enterprise case file summarization, knowledge surfacing, and adjudication with human-in-the-loop reliability, delivering material reductions in review time and cost. ### Limited Partner, Advisor, Investor @ Independent Investor & Advisor Jan 2016 – Present | San Francisco, CA Limited partner and angel investor in PE, VC, and B2B AI SaaS companies, operating hands-on as a fractional product and AI leader to founders and investment teams by setting product direction, shaping AI and data strategy, and driving enterprise GTM, while building data-driven investment infrastructure that strengthens sourcing and diligence, accelerates portfolio value creation, and makes investment operations more efficient, effective and repeatable. ### Head of Product & Innovation @ Georgian Partners Jan 2016 – Jan 2023 | Toronto, ON Head of Product & Innovation at a $6B+ AUM growth-stage B2B AI venture capital fund, led the firm-wide AI agenda across sourcing, diligence, investment thesis development, and portfolio acceleration. Built data-driven investment and diligence products and infrastructure, launched the firm’s innovation program, and codified repeatable AI value-creation playbooks spanning sales acceleration, workflow automation, and trust and governance. Led programs with portfolio product leaders to translate AI readiness frameworks into post-close roadmaps tied to commercial KPIs and board-level operating cadence, and helped scale internal product, engineering, and data capabilities while supporting technical diligence and portfolio initiatives across regulated domains. ### Chief Technology Officer (CTO) @ Idibon Jan 2015 – Jan 2016 | San Francisco, CA Led a 20+ person engineering and ML organization and owned the technical roadmap for an adaptive language intelligence platform. Built evaluation and guardrail infrastructure for human-in-the-loop NLP, including data and label observability across annotation workflows, quality controls, and systematic detection and remediation of training data issues. Shipped enterprise production systems for classification and risk scoring with measurable impact for Fortune 500 customers, including step-change improvements in customer-service routing and stronger compliance monitoring. Inventor on patents spanning human-in-the-loop ML, corpus construction, data observability, and NLP architectures that enabled reliable, repeatable AI workflows at scale. ### Senior Manager @ EY Jan 2011 – Jan 2015 | San Francisco, CA Oversaw post-acquisition integration and scaling of AI assets from a legal tech startup into EY’s global Forensic Analytics platform, establishing a repeatable foundation for new products and services across investigations, compliance, and eDiscovery. Led cross-functional teams of forensic experts and ML engineers to build and harden production NLP and ML systems for high-stakes matters including financial fraud, insider trading, MNPI leakage, FCPA, and insider threat. Architected end-to-end workflows over large-scale unstructured data using semantic search, entity normalization, graph-based link analysis, and supervised classification, and scaled predictive coding and document classification across hundreds of millions of pages. Delivered human-in-the-loop review pipelines and defensible reporting that improved auditability and materially reduced cycle time and cost through evaluation-driven reliability controls and iterative improvement loops in regulated enterprise environments. ### Voice Design Lead, Advanced Speech Design & Development @ Nuance Communications Jan 2010 – Jan 2011 | San Francisco Bay Area Pioneered end-to-end development of production text-to-speech voices for high-volume IVR and mobile experiences. Built a data-driven speech ML pipeline spanning corpus design, data capture, text selection, lexicon development, studio direction, labeling and QA, inter-annotator agreement, and release gates, and partnered with engineering to ship prosody-control and artifact-reduction improvements in the TTS engine. Established evaluation and tuning loops using MOS and ABX testing, structured listening panels, and iterative error analysis to improve perceived naturalness and reduce call friction and repair turns across enterprise and consumer deployments. ### Senior Linguist @ Cataphora Jan 2007 – Jan 2010 | San Francisco Bay Area Built and shipped production NLP and semantic search capabilities for enterprise litigation, discovery, and compliance workflows. Architected end-to-end pipelines for unstructured legal text, including topic segmentation, entity extraction, event and claims detection, and technology-assisted review workflows, and partnered directly with high-stakes legal clients to define requirements, guide deployments, and iterate based on user behavior. Developed extensible ontology and knowledge-graph tooling to adapt search and classification systems to matter-specific taxonomies, and created a web-based annotation platform to bootstrap high-quality training datasets and improve model performance in supervised and semi-supervised learning. Served as a bridge across linguistics, engineering, UI/UX, client services, and sales to translate research into deployed products. ## Education ### Stanford Natural Language Processing Group Stanford University ### Ph.D. in Linguistics University of Colorado Boulder ### Venture Studio Morrow Venture Studio Bootcamp ## Contact & Social - LinkedIn: https://linkedin.com/in/jason-brenier --- Source: https://flows.cv/jasonbrenierphd JSON Resume: https://flows.cv/jasonbrenierphd/resume.json Last updated: 2026-04-05